White balance method for shading compensation, and apparatus applied to the same

ABSTRACT

The present disclosure relates to a white balance method for performing a shading compensation, and more particularly, a white balance method for performing a shading compensation, in which a white balance control is initiated for an input image captured when a camera is driven, and then the shading compensation is performed together during a process of performing the initiated white balance control. The white balance method for performing a shading compensation includes executing a white balance for adjusting a color temperature of an input image, extracting a shading gain table corresponding to the color temperature among pre-stored shading gain tables for each color temperature during the execution of the white balance, executing a shading compensation for an image for each block of the input image by using the extracted shading gain table, and terminating the white balance.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority from Korean Patent Application No.10-2013-0079831, filed on Jul. 8, 2013 in the Korean IntellectualProperty Office, the disclosure of which is incorporated by referenceherein in its entiry.

BACKGROUND

1. Field

The present disclosure relates to a white balance method for performinga shading compensation, and more particularly, a white balance methodfor performing a shading compensation, in which a white balance controlis initiated for an input image captured when a camera is driven, andthen the shading compensation is performed together during a process ofperforming the initiated white balance control.

2. Description of the Related Art

As a number of pixels of an image sensor increases and a viewing angleof a mounted and downsized lens is widened, a diameter of the lens isdecreased which causes an incident angle of a chief ray to increase. Asa result, the brightness in the center area of an image taken throughthe lens is greater than the brightness of an area surrounding thecenter of the image, or a lens shading phenomenon is generated. The lensshading phenomenon is where colors of the area surrounding the center ofthe image are distorted.

The related art attempts to solve these problems by compensating forshading by using a separate memory, or by performing a separate imageprocessing on the image.

However, the shading compensating methods of the related art include aseparate control performing process for avoiding a shading phenomenon.Due to this separate control performing process a processing time isincreased, and a processing module for performing the separate controlperforming process for avoiding the shading phenomenon needs to beadditionally included in a chip form.

SUMMARY

The present disclosure provides a white balance method for a shadingcompensation. The white balance method uses a processing module tocontrol the white balance. The processing module performs shadingcompensation together with controlling the white balance. That is thepresent disclosure provides a processing module for controlling thewhite balance which is different from a processing module requiring aseparate process for a shading compensation.

The present disclosure is not limited to the aforementioned matters, andthose skilled in the art will clearly understand, through the followingdescription, that the present disclosure may provide other non-mentionedfeatures.

Accordingly, in the present disclosure, the processing module thatcontrol a white balance also performs a shading compensation, instead ofa different processing module performing the shading compensation as inthe related art As a result, there is an advantage in that it ispossible to prevent a processing time according to each of the whitebalance control and the shading compensation from being delayed, and itis not necessary to include an additional processing module forpreventing an image distortion due to a shading phenomenon.

One or more exemplary embodiments of the present disclosure include awhite balance method for performing a shading compensation, the methodincludes executing, using a processor, a white balance for adjusting acolor temperature of an input image; extracting, using the processor, ashading gain table corresponding to the color temperature amongpre-stored shading gain tables for each color temperature during theexecution of the white balance; executing a shading compensation for animage for each block of the input image by using the extracted shadinggain table; and terminating the white balance.

One or more exemplary embodiments of the present disclosure include awhite balance control apparatus for a shading compensation, theapparatus includes a storage module configured to store shading gaintables, so that each color temperature has a corresponding shading gaintable; and a white balance processing module configured to extract ashading gain table corresponding to a color temperature of an inputimage during an execution of a white balance for adjusting the colortemperature of the input image, and execute a shading compensation foran image for each block of the input image by using the extractedshading gain table.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features and advantages of the present disclosurewill become more apparent by describing in detail exemplary embodimentsthereof with reference to the attached drawings in which:

FIG. 1 is a diagram illustrating an exemplary embodiment of a whitebalance control apparatus according to the present disclosure;

FIG. 2 is a diagram illustrating a capture concept of a white imageaccording to an exemplary embodiment of the present disclosure;

FIG. 3 is a diagram illustrating an exemplary embodiment of a blockdivision for a captured image of FIG. 2;

FIG. 4 is a diagram illustrating an exemplary embodiment of acharacteristic curve according to the present disclosure;

FIG. 5 is a diagram illustrating an exemplary embodiment of a boundaryregion based on the characteristic curve illustrated in FIG. 4;

FIG. 6 is an exemplary embodiment of a diagram illustrating an operationprocess of the white balance control apparatus illustrated in FIG. 1;

FIG. 7 is a diagram illustrating an exemplary embodiment of an algorithmexecution process in the operation process illustrated in FIG. 6;

FIG. 8 is a diagram illustrating another exemplary embodiment of a whitebalance control apparatus according to the present disclosure; and

FIG. 9 illustrates an exemplary embodiment of a diagram illustrating anoperation process of the white balance control apparatus illustrated inFIG. 8.

DETAILED DESCRIPTION

Advantages and features of the present disclosure and methods ofaccomplishing the same may be understood more readily by reference tothe following detailed description of exemplary embodiments and theaccompanying drawings. The present disclosure may, however, be embodiedin many different forms and should not be construed as being limited tothe exemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the concept of the disclosure to thoseskilled in the art, and the present disclosure will only be defined bythe appended claims. Like reference numerals refer to like elementsthroughout the specification.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

It will be understood that when an element or layer is referred to asbeing “on”, “connected to” or “coupled to” another element or layer, itcan be directly on, connected or coupled to the other element or layeror intervening elements or layers may be present. In contrast, when anelement is referred to as being “directly on”, “directly connected to”or “directly coupled to” another element or layer, there are nointervening elements or layers present. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, components, regions, layersand/or sections, these elements, components, regions, layers and/orsections should not be limited by these terms. These terms are only usedto distinguish one element, component, region, layer or section fromanother region, layer or section. Thus, a first element, component,region, layer or section discussed below could be termed a secondelement, component, region, layer or section without departing from theteachings of the present disclosure.

Spatially relative terms, such as “beneath”, “below”, “lower”, “above”,“upper”, and the like, may be used herein for ease of description todescribe one element or feature's relationship to another element(s) orfeature(s) as illustrated in the figures. It will be understood that thespatially relative terms are intended to encompass differentorientations of the device in use or operation in addition to theorientation depicted in the figures. For example, if the device in thefigures is turned over, elements described as “below” or “beneath” otherelements or features would then be oriented “above” the other elementsor features. Thus, the exemplary term “below” can encompass both anorientation of above and below. The device may be otherwise oriented(rotated 90 degrees or at other orientations) and the spatially relativedescriptors used herein interpreted accordingly.

Exemplary Embodiments are described herein with reference tocross-section illustrations that are schematic illustrations ofidealized embodiments (and intermediate structures). As such, variationsfrom the shapes of the illustrations as a result, for example, ofmanufacturing techniques and/or tolerances, are to be expected. Thus,these exemplary embodiments should not be construed as limited to theparticular shapes of regions illustrated herein but are to includedeviations in shapes that result, for example, from manufacturing. Forexample, an implanted region illustrated as a rectangle will, typically,have rounded or curved features and/or a gradient of implantconcentration at its edges rather than a binary change from implanted tonon-implanted region. Likewise, a buried region formed by implantationmay result in some implantation in the region between the buried regionand the surface through which the implantation takes place. Thus, theregions illustrated in the figures are schematic in nature and theirshapes are not intended to illustrate the actual shape of a region of adevice and are not intended to limit the scope of the presentdisclosure.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which the present disclosure belongs. Itwill be further understood that terms, such as those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andthis specification and will not be interpreted in an idealized or overlyformal sense unless expressly so defined herein.

Hereinafter, an exemplary embodiment of the present disclosure will bedescribed in detail with reference to the accompanying drawings.

FIG. 1 is a diagram illustrating an exemplary embodiment of a whitebalance control apparatus 100 according to the present disclosure. Thewhite balance control apparatus 100 is related to a process of detectingan environmental characteristic for an image attribute, such as a colortemperature, and then performing an image interpolation processcorresponding to the detected environmental characteristic. Asillustrated in FIG. 1, the white balance control apparatus 100 includesa configuration in which a shading compensation is also performed by analgorithm controlling a white balance.

Here, the environmental characteristic is a concept based on a colorattribute of a combination including one or more of a lens system 110, aband pass filter 120, and an image sensor 130 of a camera.

To this end, when executing a shading compensation for preventing atleast one of a color and brightness of a surrounding area of an imagefrom being distorted while executing a white balance for matching theimage to an image with the color temperature conforming to theaforementioned environmental characteristic together, the white balancecontrol apparatus 100 may be divided into a plurality of configurations.The configurations include a first configuration for a preprocessing ofgenerating a shading gain table for generating a compensation value ofthe aforementioned shading compensation, and a second configuration forexecuting an algorithm executing a shading compensation during theexecution of the white balance for an actually input image.

That is, the white balance control apparatus 100 may include a whitebalance processing module 140, which is the aforementioned secondconfiguration, an image output module 160 for outputting a white balanceprocessed image on a screen, and a storage module 150 for storingvarious information for an image compensation.

Because environmental characteristics of an input image are diverse,various information stored in the storage module 150 may include ashading gain table for each color temperature capable of correspondingto various environmental characteristics

The white balance processing module 140 may extract, during theexecution of the white balance for adjusting a color temperature of theinput image, a shading gain table corresponding to the environmentalcharacteristic of the input image among the shading gain tables for eachcolor temperature stored in the storage module 150, and execute ashading compensation for an image for each block of the input image byusing the extracted shading gain table.

The input image may be an image captured through the camera.

The shading gain table for each color temperature refers to a tablegenerated based on characteristic data corresponding to a selected whiteframe by dividing a white image captured for each color temperature intoM blocks, and selecting a valid white block belonging to a predeterminedwhite frame range based on a predetermined value corresponding to thedivided N blocks.

The characteristic data may be expressed in a form of a characteristiccurve including an X axis as a value of Dr and a Y axis as a value ofDb. and hereinafter, the exemplary embodiment in which thecharacteristic data is used for the characteristic curve will bedescribed.

The characteristic curve will be described below with reference to FIGS.2 to 4.

First, in order to generate the characteristic curve, N white images arecaptured for each color temperature, each of the N white images for eachcolor temperature is divided into M small blocks, an RGB average valueis calculated for each of the M blocks, the calculated RGB average valueof the block is converted to a normalized YDrDb value, and then anaverage YDrDb value of the entire blocks is calculated by using theYDrDb value for each block.

An average YDrDb value is identically calculated for the N white imagefor each color temperature by the same method, and the N white images ofwhich the average YDrDb value is calculated for each color temperatureis indicated with a curve having the X axis as a value of Dr and the Yaxis as a value of Db.

That is, the characteristic curve is an approximation of the YDrDb valuefor each color temperature in the indicated curve to a 2-dimensionalexpression. FIGS. 4 and 5 illustrate the characteristic curve of a firstcolor temperature 405 and a second color temperature 410. As illustratedin FIG. 4, each point of the characteristic curves 405 and 410 refers toa reference point (Dr, Db) for the corresponding color temperature.

The shading gain table may include a color shading gain table and aluminance shading gain table. The color shading gain table is forcompensating for color distortion for a center area and a surroundingarea of an input image. The luminance shading gain table is forcompensating for brightness distortion for the center area and thesurrounding area of the input image.

Information about the shading gain table for each color temperature maybe already stored in the storage module 150 as a default, or may bedownloaded to the storage module 150 by accessing a related serverproviding image compensation services through a communicationconnection, such as a web connection.

The white balance processing module 140 divides the input image into Mblocks, identifies whether each of the blocks is included in a whiteframe, calculates an average RGB value and an average YDrDb based on avalid white block according to a result of the identification, and thencalculates an R gain value and a B gain value for applying the whitebalance based on the average RGB value.

Then, the white balance processing module 140 selects a matrix, a colorshading table, and a luminance shading table for each color temperatureby matching the average YDrDb value with each reference point of thecharacteristic curve and finding a color temperature of the input image,calculates an R gain value and a B gain value for each block of theinput image based on a result of the selection, and then applies thecalculated R gain value and B gain value to an image processing.

When the algorithm for the input image is applied through the presentdisclosure, a converted YCrCb value may be reconverted to the normalizedYDrDb value through an expression below.

Dr=(Cr/Y)*a,Db=(Cb/Y)*a  <Expression>

Where “a” is a normalized value.

Referring to FIG. 5, a white frame boundary region 415 based on thecharacteristic curves may be confirmed. That is, in a case where theYDrDb value of each block is applied to the point (Dr, Db) on thecharacteristic curve, and is positioned within the aforementioned whiteframe boundary region 415, the YDrDb value may be acknowledged as avalid white value.

In a case where the algorithm of the present disclosure is applied, whenthe input image is divided into M blocks, the YDrDb value for each blockis converted, and the converted YDrDb value is applied to a point (Dr,Db) on a corresponding characteristic curve, whether each YDrDb value ispositioned within the white frame boundary region 415 based on thecharacteristic curve is identified, and then only the block positionedwithin the white frame boundary region 415 is recognized as the whiteblock, and an average RGB value and an average YDrDb value of the blockswhich are identified as the valid white blocks are calculated.

Based on information stored in the storage module 150 the white balanceprocessing module 140 divides an input image, which is input when thecamera is driven, into an image for each block, then the white balanceprocessing module 140 performs a white balance compensation whileexecuting the shading compensation. The shading compensation applies aseparate color gain compared to that for the center for the dividedimage for each block.

FIG. 6 is a diagram illustrating an operation process of the whitebalance control apparatus 100 illustrated in FIG. 1. As illustrated inFIG. 6, the white balance control apparatus 100 initiates a whitebalance for an input image input when the camera is driven (S100 andS102).

Then, the white balance, which compensates for the image in accordancewith a color temperature conforming to an environment in which thecamera captures the image, is performed, and during the performance ofthe white balance a shading compensation function for compensating for adistortion of a surrounding area of the image is activated (S104).

In a case where the image passing through the white balance controlalgorithm of step S104 is output on the screen, the image, on which boththe white balance and the shading compensation have been performed, isoutput on the screen (S106 and S108).

Then, when the driving of the camera is terminated, the performance ofthe aforementioned respective steps is also terminated (S110).

A detailed process (S104) of performing the shading compensation duringthe execution of the white balance will be described with reference toFIG. 7.

That is, the white balance method for performing the shadingcompensation may include executing the white balance for adjusting thecolor temperature of the input image (S104-1), extracting a shading gaintable corresponding to the color temperature among the pre-storedshading gain tables for each color temperature during the execution ofthe white balance (S104-3), executing the shading compensation for theimage for each block of the input image by using the extracted shadinggain table (S104-5), and terminating the currently executed whitebalance (S104-7).

Extracting a shading gain table (S104-3) is started by dividing theinput image, which is input when the camera is driven, into M blocks,and calculating an RGB average value for each divided block.

Then, the RGB average value for each block is converted to the YDrDbvalue, and the converted YDrDb value for each block is applied to apredetermined white frame to select a valid white block.

Then, the valid white blocks are selected by applying the YDrDb valuefor each block to the predetermined white frame, a YDrDb average valuefor the YDrDb values of the selected white blocks is calculated, aposition on the characteristic curve corresponding to the calculatedYDrDb average value is specified, and then a matrix, a color shadinggain table, and a luminance shading gain table are selected based on thespecified point.

In the meantime, in executing the shading compensation (S104-5), areference R gain value and a reference B gain value are calculated basedon the RGB average value of the valid white block for the input image.The an R gain value and a B gain value for each block are calculated byapplying the reference R gain value and the reference B gain value tothe shading gain table.

Then, the R gain value and the B gain value for each block are dividedinto a Y signal and a C signal, and the shading compensation isperformed on at least one of the divided Y signal and C signal.

That is, the calculated R gain value and B gain value are calculated as“an R1 value, a G1 value, and a B1 value” based on the RGB average valuecalculated through the white frame and through an RGB to RGB conversionmatrix.

Then, “R1 gain value=G1 value/R1 value, and B1 gain value=G1 value/B1value” are calculated, and the R gain value and the B gain value may becalculated through expressions below.

R gain value=R1 gain value*Rn gain value,B gain value=B1 gain value*Bngain value  <Expression>

Where Rn gain value=R gain value for each block, and Bn gain value=Bgain value for each block.

Then, the R gain value and the B gain value for each block are dividedinto a Y signal, which is a color signal for brightness, and a C signal,which is a color signal for a color, and the shading compensation isperformed on at least one of the divided Y signal and C signal.

FIG. 8 is a diagram illustrating another exemplary embodiment of a whitebalance control apparatus 200 according to the present disclosure. Asillustrated in FIG. 8, the white balance control apparatus 200 maydetermine whether a color attribute by a combination of one or more of alens system, a band pass filter, and an image sensor is changed when acamera is driven.

In a case where the color attribute is changed according to the resultof the determination when the camera is driven, the white balancecontrol apparatus 200 additionally determines whether information abouta characteristic curve and a shading gain table corresponding to thechanged color attribute (or, also referred to as an image attribute) isincluded.

When the information about the characteristic curve and the shading gaintable corresponding to the changed color attribute (or, also referred toas the image attribute) is not included according to the result of theadditional determination, a process of generating the information aboutthe characteristic curve and the shading gain table corresponding to thechanged color attribute (or, also referred to as the image attribute) isfurther executed.

The determination as to whether the color attribute is changed and thegeneration of the information about the characteristic curve and theshading gain table corresponding to the changed color attribute (or,also referred to as the image attribute) may be executed by an imageattribute determination module 260 additionally included to the whitebalance control apparatus 200, or may be performed by the white balanceprocessing module 240 mentioned in the exemplary embodiment of FIG. 1.

In the determination as to whether the color attribute is changed or thegeneration of the information about the characteristic curve and theshading gain table corresponding to the changed color attribute (or,also referred to as the image attribute) by the image attributedetermination module 260 or the white balance processing module 240, aprocess of capturing a white image for each color temperature for theinput image when the camera is driven, dividing the captured white imageinto N blocks, and calculating an RGB average value for each dividedblock is performed.

Then, an RGB average value of the entire blocks is calculated based onthe RGB average value for each block, the RGB average value of theentire blocks is converted to a normalized YCrCb value, and then anormalized YDrDb value for an Y signal is calculated in order to removean error for a change in a size of a CrCb value for the Y signal.

The converted YCrCb value may be reconverted to the normalized YDrDbvalue through an expression below.

Dr=(Cr/Y)*a,Db=(Cb/Y)*a  <Expression>

Where “a” is a normalized value.

A YDrDb value of the average of the entire blocks is calculated by usingthe YDrDb value for each block, and then a YDrDb table for each colortemperature is generated by applying the YDrDb value of the average ofthe entire blocks to the input image for each color temperature.

Then, the characteristic curve in accordance with a white balancecontrol environment may be calculated through the generated YDrDb tablefor each color temperature.

When a reference point of the characteristic curve for each colortemperature is specified according to projection of the YDrDb value foreach color temperature measured when the camera is driven, thecharacteristic curve calculated as described above is used for a methodof matching an RGB to RGB conversion matrix with a shading gain tablefor each color temperature based on the specified reference point.

FIG. 9 is a diagram illustrating an operation process of the whitebalance control apparatus 200 illustrated in FIG. 8 as an exemplaryembodiment. As illustrated in FIG. 8, the white balance controlapparatus 200 may determine whether a color attribute is changed whenthe camera is driven by a combination of one or more of a lens system, aband pass filter, and an image sensor (S200 and S202).

In response to the image attribute changing (Y at S202), a process ofsetting a characteristic curve and a shading gain table based on achanged white balance control environment is executed (S204 and S206).

In setting the characteristic curve and the shading gain table (S206),the characteristic curve and the shading gain table corresponding to thechanged image attribute may not be included. In such a case, a furtherprocess of generating information about the characteristic curve and theshading gain table corresponding to the changed image attribute isperformed.

When a white balance for the input image of the camera is initiated(S208), a shading gain table corresponding to a characteristic curve formeasuring the corresponding white balance control environment asspecific data is extracted, and then the shading compensation isperformed while performing the white balance control based on theextracted shading gain table (S210).

When the image passing through the white balance control algorithm of(S210) is output on a screen, the image on which the white balance andthe shading compensation are performed is output on the screen (S212 andS214).

Then, when the driving of the camera is terminated, the performance ofthe aforementioned processes are also terminated (S216).

The foregoing is illustrative of the present disclosure and is not to beconstrued as limiting thereof. Although a few exemplary embodiments ofthe present disclosure have been described, those skilled in the artwill readily appreciate that many modifications are possible in theexemplary embodiments without materially departing from the novelteachings and advantages of the present disclosure. Accordingly, allsuch modifications are intended to be included within the scope of thepresent disclosure as defined in the claims. Therefore, it is to beunderstood that the foregoing is illustrative of the present disclosureand is not to be construed as limited to the specific exemplaryembodiments disclosed, and that modifications to the disclosed exemplaryembodiments, as well as other embodiments, are intended to be includedwithin the scope of the appended claims. The present disclosure isdefined by the following claims, with equivalents of the claims to beincluded therein.

What is claimed is:
 1. A white balance method for performing a shadingcompensation, the method comprising: executing, using a processor, awhite balance for adjusting a color temperature of an input image;extracting, using the processor, a shading gain table corresponding tothe color temperature among pre-stored shading gain tables for eachcolor temperature during the execution of the white balance; executing ashading compensation for an image for each block of the input image byusing the extracted shading gain table; and terminating the whitebalance.
 2. The white balance method of claim 1, further comprising:generating a shading gain table for each color temperature.
 3. The whitebalance method of claim 1, wherein the shading compensation applies aseparate color gain compared to that for a center for the image for eachblock of the input image by using the extracted shading gain table. 4.The white balance method of claim 2, wherein the shading compensationapplies a separate color gain compared to that for a center for theimage for each block of the input image by using the extracted shadinggain table.
 5. The white balance method of claim 2, wherein thegenerating of the shading gain table for each color temperatureincludes: capturing a white image for each color temperature; dividingthe captured white image into M blocks, and calculating an RGB averagevalue for each of the M blocks; converting the RGB average value foreach of the M blocks to a normalized YCrCb value, and reconverting thenormalized YCrCb value to a normalized YDrDb value; calculating a YDrDbaverage value by averaging the normalized YDrDb values from each of theM blocks; calculating a YDrDb table for each color temperature byapplying the YDrDb average value to each color temperature; andselecting a valid white frame by using the YDrDb table for each colortemperature, and generating the shading gain table for each colortemperature based on characteristic data corresponding to the selectedframe.
 6. The white balance method of claim 1, wherein the extracting ofthe shading gain table includes: dividing the input image into M blocks,and calculating an RGB average value for each of the M blocks;converting the RGB average value for each of the M blocks to a YDrDbvalue; selecting a valid white block corresponding to a predeterminedwhite frame based on the YDrDb value; calculating a YDrDb average valuefor the YDrDb value for each selected white block; determiningcharacteristic data including the YDrDb average value; and extracting ashading gain table corresponding to the characteristic data among theshading gain tables for each color temperature.
 7. The white balancemethod of claim 2, wherein the extracting of the shading gain tableincludes: dividing the input image into M blocks, and calculating an RGBaverage value for each of the M blocks; converting the RGB average valuefor each of the M blocks to a YDrDb value; selecting a valid white blockcorresponding to a predetermined white frame based on the YDrDb value;calculating a YDrDb average value for the YDrDb value for each selectedwhite block; determining characteristic data including the YDrDb averagevalue; and extracting a shading gain table corresponding to thecharacteristic data among the shading gain tables for each colortemperature.
 8. The white balance method of claim 1, wherein theexecuting of the shading compensation includes: calculating a referenceR gain value and a reference B gain value based on the RGB average valueof the valid white block for the input image; calculating an R gainvalue and a B gain value for each block by applying the reference R gainvalue and the reference B gain value to the shading gain table; dividingthe R gain value and the B gain value for each block to a Y signal and aC signal; and executing a shading compensation for at least one of the Ysignal and the C signal.
 9. The white balance method of claim 2, whereinthe executing of the shading compensation includes: calculating areference R gain value and a reference B gain value based on the RGBaverage value of the valid white block for the input image; calculatingan R gain value and a B gain value for each block by applying thereference R gain value and the reference B gain value to the shadinggain table; dividing the R gain value and the B gain value for eachblock to a Y signal and a C signal; and executing a shading compensationfor at least one of the Y signal and the C signal.
 10. A white balancecontrol apparatus for a shading compensation, the apparatus comprising:a storage module configured to store shading gain tables, so that eachcolor temperature has a corresponding shading gain table; and a whitebalance processing module configured to extract a shading gain tablecorresponding to a color temperature of an input image during anexecution of a white balance for adjusting the color temperature of theinput image, and execute a shading compensation for an image for eachblock of the input image by using the extracted shading gain table. 11.The white balance control apparatus of claim 10, wherein the extractedshading gain table is generated based on characteristic datacorresponding to a selected white frame by dividing a white imagecaptured for each color temperature into M blocks, and selecting a validwhite block belonging to a predetermined white frame range based on apredetermined value corresponding to the M blocks.
 12. The white balancecontrol apparatus of claim 11, wherein the predetermined value is an RGBaverage value of each of the M blocks, and the RGB average value isconverted to a value for selecting the white block by performing a YCrCbconversion and a YDrDb conversion.
 13. The white balance controlapparatus of claim 10, wherein the white balance processing moduledivides the input image into M blocks, selects a valid white blockbelong to a predetermined white frame range among the M blocks,determines characteristic data corresponding to the selected whiteblock, and extracts a shading gain table corresponding to thecharacteristic data from among the stored shading gain tables.
 14. Thewhite balance control apparatus of claim 10, wherein the white balanceprocessing module calculates a reference R gain value and a reference Bgain value based on the RGB average value of a valid white block for theinput image, calculates an R gain value and a B gain value for eachblock by applying the reference R gain value and the reference B gainvalue to the shading gain table; divides the R gain value and the B gainvalue for each block to a Y signal and a C signal; and executes ashading compensation for at least one of the Y signal and the C signal.15. A white balance control apparatus for a shading compensation, theapparatus comprising: a storage module configured to store a shadinggain table corresponding to a color temperature; and a white balanceprocessing module configured to execute a shading compensation of aninput image by using the shading gain table while also executing a whitebalance for adjusting the color temperature of the input image.
 16. Thewhite balance control apparatus according to claim 15, wherein the inputimage includes a center area and an area that is adjacent to the centerarea, and in executing the shading compensation of the input image thewhite balance processing module applies a first color gain to the centerarea and a second color gain different from the first color gain to thearea adjacent to the center area.
 17. The white balance controlapparatus according to claim 15, wherein the white balance processingmodule executes the shading compensation of the input image by dividingthe input image into M blocks, calculating an RGB average value for eachof the M blocks, converting the RGB average value for each of the Mblocks to a YDrDb value, selecting a valid white block corresponding toa predetermined white frame based on the YDrDb value, calculating aYDrDb average value for the YDrDb value for each selected white block,determining characteristic data including the YDrDb average value; andextracting a shading gain table corresponding to the characteristic dataamong the shading gain tables for each color temperature.